A method for monitoring the operating state of an energy storage energy management system

Abstract

The application relates to the technical field of energy storage state monitoring, in particular to a running state monitoring method of an energy storage energy management system, which comprises the following steps: acquiring voltage sequences and internal resistance sequences of each single energy storage battery and an energy storage battery group; acquiring voltage abnormal weight of each single energy storage battery according to voltage data fluctuation characteristics of each single energy storage battery, differences in voltage change rates between each single energy storage battery and all other single energy storage batteries and differences in voltage ranges, and acquiring running abnormal factors of each single energy storage battery by combining trend item data of internal resistance data of each single energy storage battery, fluctuation characteristics and nonlinear characteristics of internal resistance sequences of each single energy storage battery and similarity degrees of internal resistance data between each single energy storage battery and all other single energy storage batteries, so as to judge whether the energy storage battery group is running abnormally. The application improves the running state monitoring accuracy of the energy storage battery group by more accurately analyzing the characteristics of each single energy storage battery in an abnormal state.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage state monitoring, and particularly relates to a running state monitoring method of an energy storage energy management system. BACKGROUND

[0002] The running state monitoring of the energy storage energy management system refers to that through various sensors, monitoring devices, Internet of Things or data acquisition and processing technologies, various key parameters and device running information in the energy storage system are acquired in real time and accurately, data analysis technologies are used to realize comprehensive grasping and effective monitoring of the running state of the energy storage system, and potential faults and abnormalities are found in time.

[0003] The BMS battery management system is an important part of the energy storage energy management system EMS, and the running state monitoring thereof is an important link for ensuring stable operation of the EMS system and improving efficiency. In the prior art, when the running state of the energy storage battery pack is monitored, the differences between the capacity attenuation rates of different batches of battery cells are not considered, the cluster-level battery monitoring can cover up the abnormality of the single battery, and thus the running state monitoring result of the energy storage battery pack has errors. Meanwhile, in the parallel structure of the energy storage battery pack, the nonlinear and irrelevant relationship of the internal resistance data of the energy storage battery caused by the temperature influence, and the internal resistance abnormality of the single energy storage battery caused by the extreme temperature can also cause the internal resistance of the energy storage battery pack to have monitoring errors, and thus the accuracy of the running state monitoring result of the energy storage battery pack is low. SUMMARY

[0004] In order to solve the above technical problems, the present application provides a running state monitoring method of an energy storage energy management system to solve the existing problems.

[0005] The running state monitoring method of the energy storage energy management system provided by the present application adopts the following technical scheme:

[0006] One embodiment of the present application provides a running state monitoring method of an energy storage energy management system, which comprises the following steps:

[0007] The voltage sequence and the internal resistance sequence of each single energy storage battery are acquired, and the voltage sequence and the internal resistance sequence of the energy storage battery pack are acquired;

[0008] According to the voltage change rate of each single energy storage battery in the neighborhood of each mutation point in the voltage sequence of each single energy storage battery, a voltage change rate sequence of each single energy storage battery is obtained; according to the similarity degree of the position sequence of the mutation point in the voltage sequence of each single energy storage battery and the position sequence of the mutation point in the voltage sequence of the energy storage battery group, and the distance between the voltage change rate sequence of each single energy storage battery and the voltage change rate sequence of all other single energy storage batteries, a response rate consistency of each single energy storage battery is obtained, and in combination with the difference between the discrete degrees of the voltage sequences of each single energy storage battery and the energy storage battery group, and the difference between the voltage ranges of each single energy storage battery and all other single energy storage batteries, a voltage abnormality weight of each single energy storage battery is obtained;

[0009] According to the trend item intensity of each internal resistance data in the internal resistance sequence of each single energy storage battery and the energy storage battery group, an internal resistance trend sequence of each single energy storage battery and the energy storage battery group is obtained; according to the autocorrelation degree of the internal resistance trend sequence corresponding to each single energy storage battery and the energy storage battery group, and the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of each single energy storage battery, a trend fluctuation intensity of each single energy storage battery is obtained, and in combination with the distance between all data in the internal resistance sequence of each single energy storage battery and the fitting straight line thereof, and the similarity degree between the internal resistance sequence of each single energy storage battery and the internal resistance sequence of all other single energy storage batteries, an internal resistance abnormality factor of each single energy storage battery is obtained, and in combination with the voltage abnormality weight of each single energy storage battery, an operation abnormality factor of each single energy storage battery is obtained, and then it is judged whether the energy storage battery group is abnormal in operation.

[0010] Preferably, the process of obtaining the voltage change rate sequence of each single energy storage battery is as follows: all mutation points in the voltage sequence of each single energy storage battery are obtained; all voltage data between each mutation point and the previous mutation point in the voltage sequence are sequentially arranged to form an instantaneous voltage sequence of each mutation point; the ratio of the absolute value of the difference between the head and tail voltage data of each instantaneous voltage sequence to the duration thereof is taken as the instantaneous voltage change rate of each instantaneous voltage sequence; and the sequence of the instantaneous voltage change rates of all instantaneous voltage sequences corresponding to each single energy storage battery is taken as the voltage change rate sequence of each single energy storage battery.

[0011] Preferably, the process of obtaining the response rate consistency of each single energy storage battery is as follows:

[0012] According to the position sequence of all mutation points in each voltage sequence, a mutation sequence of each voltage sequence is obtained;

[0013] The response rate consistency of each single energy storage battery is calculated as follows: ; in the formula, is the response rate consistency of the i th single energy storage battery, is the cosine similarity between the mutation sequence of the voltage sequence of the energy storage battery group and the mutation sequence of the voltage sequence of the i th single energy storage battery, The DTW distance accumulation result between the voltage variation rate sequence corresponding to the i-th single energy storage battery and all the other single energy storage batteries in the energy storage battery pack.

[0014] Preferably, the mutation sequence of each voltage sequence refers to the sequence composed of the positions of all the mutation points in each voltage sequence.

[0015] Preferably, the calculation formula of the voltage abnormality weight of each single energy storage battery is: ; wherein, is the voltage abnormality weight of the i-th single energy storage battery, is the ratio between the variance of the voltage sequence corresponding to the i-th single energy storage battery and the energy storage battery pack, is the absolute value accumulation result between the voltage range corresponding to the i-th single energy storage battery and all the other single energy storage batteries in the energy storage battery pack; is the response rate consistency of the i-th single energy storage battery, and norm() is a normalization function.

[0016] Preferably, the internal resistance trend sequence of each single energy storage battery and the energy storage battery pack refers to the sequence composed of the trend item intensity of all the internal resistance data in the internal resistance sequence of each single energy storage battery and the energy storage battery pack in chronological order.

[0017] Preferably, the calculation formula of the trend fluctuation intensity of each single energy storage battery is: ; wherein, is the trend fluctuation intensity of the i-th single energy storage battery, , are respectively the Hurst index of the internal resistance trend sequence of the i-th single energy storage battery and the energy storage battery pack, is the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of the i-th single energy storage battery.

[0018] Preferably, the calculation formula of the internal resistance abnormality factor of each single energy storage battery is: ; wherein, is the internal resistance abnormality factor of the i-th single energy storage battery; is the trend fluctuation intensity of the i-th single energy storage battery, is the accumulation result of the shortest distance between all the data in the internal resistance sequence of the i-th single energy storage battery and the fitted straight line thereof, is the accumulation result of the Pearson similarity coefficient between the internal resistance sequence of the i-th single energy storage battery and all the other single energy storage batteries in the energy storage battery pack.

[0019] Preferably, the calculation formula of the operation abnormality factor of each single energy storage battery is: ; wherein, an operating abnormality factor of the i-th single energy storage battery; a voltage abnormality weight of the i-th single energy storage battery in the energy storage battery pack; an internal resistance abnormality condition of the i-th single energy storage battery in the energy storage battery pack; norm() is a normalization function.

[0020] Preferably, the specific process of judging whether the energy storage battery pack is in an abnormal operating state is that when the number of single energy storage batteries in the energy storage battery pack whose operating abnormality factor is greater than or equal to a preset abnormality threshold value exceeds a preset proportion, it is judged that the energy storage battery pack is in an abnormal operating state; otherwise, it is judged that the energy storage battery pack is not in an abnormal operating state.

[0021] The present application has at least the following beneficial effects:

[0022] 1. The present application is aimed at the problem that the shielding effect of the energy storage battery pack on the voltage and internal resistance monitoring of the single energy storage battery in the battery management unit under the energy storage energy management system is serious, and the operating state of the energy storage battery pack cannot be accurately evaluated. The voltage abnormality weight and internal resistance abnormality factor of the single energy storage battery are constructed, which more accurately reflects the voltage dispersion condition of the single energy storage battery and the consistency with the response change rate of the energy storage battery pack, as well as the nonlinear and unrelated change trend of the single energy storage battery caused by the influence of extreme temperature and temperature conduction, so that the abnormal state evaluation result of each single energy storage battery is more accurate.

[0023] 2. The operating abnormality factor is obtained through the voltage abnormality weight and the internal resistance abnormality factor, and the operating state of the energy storage battery pack is evaluated based on this, which effectively avoids the masking condition of the cluster-level energy storage unit on the voltage and internal resistance abnormality condition of the single energy storage battery in the energy storage energy management system running process, and can effectively represent the overall operating state of the energy storage battery pack, and more accurately judge whether the energy storage battery pack in the energy storage energy management system is in an abnormal operating condition. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0025] Figure 1 A step flow chart of an operating state monitoring method of an energy storage energy management system provided by the present application;

[0026] Figure 2 A process of obtaining an operating abnormality factor of each single energy storage battery provided by the present application. DETAILED DESCRIPTION

[0027] To further clarify the technical means and effects taken by the present application to achieve the predetermined object of the application, the following describes in detail the specific implementation, structure, features and effects of a method for monitoring the operating state of a energy storage energy management system according to the present application, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0029] The specific scheme of the method for monitoring the operating state of a energy storage energy management system provided by the present application is described in detail below in combination with the accompanying drawings.

[0030] One embodiment of the present application provides a method for monitoring the operating state of a energy storage energy management system, specifically, the following method for monitoring the operating state of a energy storage energy management system is provided, please refer to Figure 1 The method comprises the following steps:

[0031] Step one: Obtain the voltage sequence and internal resistance sequence of each single energy storage battery; obtain the voltage sequence and internal resistance sequence of the energy storage battery pack.

[0032] The present application deploys sensors in the BMS battery management system in the energy storage energy management system to obtain relevant data during the operation of the energy storage battery. Specifically, a voltage sensor and a current sensor are deployed on each single energy storage battery in the BMS battery management system. The voltage data and current data of each single energy storage battery at each time are collected by the voltage sensor and the current sensor, and the voltage and current data sampling frequency is set to 8KHz. At the same time, the voltage and current of the energy storage battery pack composed of all single energy storage batteries at each time are collected. The open circuit voltage of the energy storage battery pack is obtained by the BMS battery management system.

[0033] The data of the single energy storage battery and the energy storage battery pack obtained above are time-synchronized according to the PTP protocol to ensure that the data timestamps are aligned. A sliding window filtering algorithm is used to filter the voltage data and current data of each single energy storage battery and the voltage data and current data of the energy storage battery pack, wherein the filtering window width is set to 5ms to eliminate voltage and current sudden change interference. Since the sliding window filtering algorithm is a known technology, the specific acquisition process will not be described in detail.

[0034] The ratio of the voltage and the current of each monomer energy storage battery at each time is taken as the internal resistance of each monomer energy storage battery at each time; and the ratio of the voltage and the current of the energy storage battery pack at each time is taken as the internal resistance of the energy storage battery pack at each time. The sequence composed of the voltage data and the internal resistance data of each monomer energy storage battery in chronological order is recorded as the voltage sequence and the internal resistance sequence of each monomer energy storage battery; and the sequence composed of the voltage data and the internal resistance data of the energy storage battery pack in chronological order is recorded as the voltage sequence and the internal resistance sequence of the energy storage battery pack.

[0035] At this point, the voltage sequence and the internal resistance sequence of each monomer energy storage battery and the energy storage battery pack in the energy storage energy management system can be obtained by the above method.

[0036] Step two: the voltage rate of change sequence of each monomer energy storage battery is obtained according to the voltage change rate in the neighborhood range of each mutation point in the voltage sequence of each monomer energy storage battery; the response rate consistency of each monomer energy storage battery is obtained according to the similarity degree of the mutation point position sequence in the voltage sequence of each monomer energy storage battery and the mutation point position sequence in the voltage sequence of the energy storage battery pack, the distance of the voltage rate of change sequence between each monomer energy storage battery and all other monomer energy storage batteries; and the voltage abnormality weight of each monomer energy storage battery is obtained by combining the difference in the dispersion degree of the voltage sequence of each monomer energy storage battery and the energy storage battery pack, and the difference in the voltage range of each monomer energy storage battery and all other monomer energy storage batteries.

[0037] In the energy storage energy management system, overcharging and overdischarging of energy storage batteries are the fundamental solution to the problem of battery pack consistency. However, due to the difference in capacity attenuation rate between different batches of cells, and the large number of monomer energy storage batteries in the energy storage battery pack, the abnormality of monomer batteries may be covered up by the running state of cluster-level energy storage units, causing the monomer batteries to reach the overcharging and overdischarging state while the cluster-level energy storage units are in good monitoring state, aggravating the battery imbalance phenomenon of the energy storage battery pack and the aging process of the monomer energy storage batteries, shortening the service life of the energy storage units, and seriously affecting the stable operation and overall performance of the energy storage energy management system.

[0038] Specifically, in the energy storage battery pack, the more serious the covering condition of the abnormality of monomer energy storage batteries by the running state of cluster-level energy storage units, the more the dispersion degree of the energy storage voltage between each monomer energy storage battery caused by the ring current forced voltage balance of the parallel battery structure, and the greater the voltage range difference between the monomer energy storage batteries caused by the difference in battery capacity; at the same time, due to the difference in capacity attenuation rate, the greater the difference in voltage change rate between each monomer energy storage battery constituting the energy storage battery pack, and the stronger the inconsistency in voltage change response between the energy storage battery pack and the monomer energy storage batteries.

[0039] Based on the above analysis, the application constructs a voltage anomaly weight for characterizing the degree of masking of the cluster-level voltage in the battery management system to the anomaly of the single energy storage battery. The difference between the maximum value and the minimum value in the voltage sequence corresponding to each single energy storage battery is recorded as the voltage range of each single energy storage battery. The voltage sequence of each single energy storage battery is taken as the input, and the Bayesian online changepoint detection algorithm (Bayesian Online Changepoint Detection) is used to obtain all the mutation points in the voltage sequence of each single energy storage battery. Similarly, all the mutation points in the voltage sequence of the energy storage battery pack are obtained.

[0040] All the voltage data between each mutation point and the previous mutation point in the voltage sequence of the single energy storage battery are arranged in time sequence to form a sequence recorded as the instantaneous voltage sequence of each mutation point (it should be noted that when there is no mutation point in front of the mutation point, i.e., the mutation point is the first mutation point, then all the data between the first voltage data and the first mutation point in the voltage sequence are arranged in time sequence to form a sequence recorded as the instantaneous voltage sequence of the first mutation point). The ratio of the absolute value of the difference between the head and tail voltage data of each instantaneous voltage sequence to the duration is recorded as the instantaneous voltage change rate of each instantaneous voltage sequence. The sequence composed of the instantaneous voltage change rates of all the instantaneous voltage sequences corresponding to each single energy storage battery is recorded as the voltage change rate sequence of each single energy storage battery. The sequence composed of the positions of all the mutation points in each voltage sequence is recorded as the mutation sequence of each voltage sequence.

[0041] In this embodiment, the response rate consistency of the i-th single energy storage battery is recorded as , and its expression is: ; in the formula, is the response rate consistency of the i-th single energy storage battery, is the cosine similarity between the mutation sequence of the voltage sequence of the energy storage battery pack and the mutation sequence of the voltage sequence of the i-th single energy storage battery, is the DTW distance accumulation result between the voltage change rate sequence corresponding to the i-th single energy storage battery and all the other single energy storage batteries in the energy storage battery pack. The response rate consistency represents the difference in instantaneous voltage change rate between the single energy storage batteries and the consistency degree of voltage change response between the energy storage battery pack and the single energy storage battery.

[0042] As a preferred embodiment, according to the response rate consistency of each single energy storage battery, the difference in the dispersion degree of the voltage sequence of each single energy storage battery and the energy storage battery pack, and the difference in the voltage range between each single energy storage battery and all the other single energy storage batteries, the voltage anomaly weight of each single energy storage battery is obtained for characterizing the anomaly degree of the voltage data of each single energy storage battery.

[0043] In this embodiment, the voltage abnormality weight of the ith single energy storage battery is denoted as , and the specific expression is: ; wherein, is the voltage abnormality weight of the ith single energy storage battery, is the ratio between the variance of the ith single energy storage battery and the corresponding voltage sequence of the energy storage battery pack, is the absolute value accumulation result of the difference between the voltage range of the ith single energy storage battery and the corresponding voltage range of all the other single energy storage batteries in the energy storage battery pack; is the response rate consistency of the ith single energy storage battery, and norm() is a normalization function, so that the value of is within the range of [0, 1].

[0044] The voltage abnormality weight reflects the degree of voltage dispersion difference of the single energy storage battery caused by the influence of the cluster-level voltage on the single energy storage battery abnormality and the inconsistency of the voltage response rate of the single energy storage battery; reflects the voltage dispersion of the single energy storage battery on the basis of the voltage stability of the energy storage battery pack; reflects the difference degree of the voltage range between the single energy storage batteries. In the process of running the EMS battery management system, when the abnormal condition of the ith single energy storage battery is more serious, the voltage dispersion of the ith single energy storage battery is larger on the basis of the voltage stability of the energy storage battery pack, and the difference of the voltage range between the single energy storage batteries in the energy storage battery pack is larger, that is, the calculated index is larger; at the same time, the consistency of the voltage response change time between the energy storage battery pack and the single energy storage battery caused by the different capacity attenuation rates of the battery is lower, and the difference of the voltage change rate between the single energy storage batteries in the energy storage battery pack is larger, that is, the calculated index is smaller.

[0045] At this point, the voltage abnormality weight of any single energy storage battery in the energy storage battery pack can be obtained by the above method.

[0046] Step three: obtaining the internal resistance trend sequence of each single energy storage battery and the energy storage battery pack according to the trend item intensity of each internal resistance data in the internal resistance sequence of each single energy storage battery and the energy storage battery pack; obtaining the trend fluctuation intensity of each single energy storage battery according to the autocorrelation degree of the internal resistance trend sequence corresponding to each single energy storage battery, the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of each single energy storage battery, and combining the distance between all data in the internal resistance sequence of each single energy storage battery and the fitting straight line thereof, and the internal resistance sequence similarity degree between each single energy storage battery and all other single energy storage batteries, obtaining the internal resistance abnormal factor of each single energy storage battery, and combining the voltage abnormal weight of each single energy storage battery to obtain the operation abnormal factor of each single energy storage battery, and then judging whether the energy storage battery pack is running abnormally.

[0047] In the energy storage battery pack composed of single energy storage batteries in parallel structure, the temperature conduction influence will cause the temperature-internal resistance dynamic coupling effect between single energy storage batteries. There are still some disadvantages in evaluating the running state of the energy storage battery in the energy storage energy management system only through the voltage abnormal weight of the single energy storage battery, without considering that the temperature difference of the energy storage battery will cause the internal resistance change condition, lacking the analysis of the nonlinear negative correlation between the internal resistance and the temperature in the charging and discharging behavior process of the energy storage battery, leading to the inability to accurately evaluate the overcharging and overdischarging risk of the energy storage battery, and affecting the running state monitoring result of the energy storage energy management system.

[0048] Specifically, during the operation of the energy storage battery pack, the more serious the internal resistance abnormal condition of the single energy storage battery caused by the extreme temperature is, and the more serious the shielding effect of the cluster-level internal resistance monitoring is, the more blurred the internal resistance change trend intensity of the energy storage battery pack is, but the more obvious the internal resistance change trend of the single energy storage battery is, and the higher the internal resistance fluctuation frequency of the single energy storage battery is; at the same time, the more significant the nonlinear correlation condition caused by the influence of the extreme temperature on the energy storage battery pack and the temperature conduction.

[0049] Based on the above analysis, the internal resistance abnormality factor of the present application is constructed to represent the serious condition of the shielding effect of the cluster level internal resistance on the internal resistance abnormality of the single energy storage battery in the battery management system. The internal resistance sequence of each single energy storage battery and the internal resistance sequence of the energy storage battery pack are respectively taken as the input of the STL (Seasonal and Trend decomposition using Loess) sequence decomposition algorithm to obtain the trend item intensity of each internal resistance data in the internal resistance sequence of the single energy storage battery and the energy storage battery pack. A sequence composed of the trend item intensity of all internal resistance data in the internal resistance sequence of each single energy storage battery in the time sequence order is recorded as the internal resistance trend sequence of each single energy storage battery. A sequence composed of the trend item intensity of all internal resistance data in the internal resistance sequence of the energy storage battery pack in the time sequence order is recorded as the internal resistance trend sequence of the energy storage battery pack. The first order difference sequence of the internal resistance sequence corresponding to the single energy storage battery is obtained, and the zero crossing rate of the first order difference sequence is counted. The internal resistance sequence of each single energy storage battery is taken as the input, and the least square method is used to obtain the fitting straight line of the internal resistance sequence of each single energy storage battery.

[0050] In the embodiment, the trend fluctuation intensity of the i-th single energy storage battery is recorded as , and the specific expression is: ; in the formula, is the trend fluctuation intensity of the i-th single energy storage battery, , Hurst index of the internal resistance trend sequence of the i-th single energy storage battery and the energy storage battery pack, respectively. When the Hurst index is closer to 0.5, it represents that the random walk nature of the data sequence is stronger. When the Hurst index is not close to 0.5, it represents that the internal resistance trend sequence has more correlation, and the internal resistance data has more obvious trend. is the zero crossing rate of the first order difference sequence of the internal resistance sequence of the i-th single energy storage battery.

[0051] The trend fluctuation degree reflects the trend intensity and internal resistance fluctuation frequency intensity of the single energy storage battery on the basis of no obvious change trend of the internal resistance of the energy storage battery pack.

[0052] As a preferred embodiment, the internal resistance abnormality factor of each single energy storage battery is obtained according to the trend fluctuation intensity of each single energy storage battery, the distance between all data in the internal resistance sequence of each single energy storage battery and the fitting straight line thereof, and the internal resistance sequence similarity between each single energy storage battery and all other single energy storage batteries, to represent the abnormality degree of the internal resistance data of each single energy storage battery.

[0053] In the embodiment, the internal resistance abnormality factor of the i-th single energy storage battery in the energy storage battery pack is recorded as , and the specific expression is: ; in the formula, the internal resistance abnormality factor of the i-th single energy storage battery; the trend fluctuation intensity of the i-th single energy storage battery, the cumulative result of the shortest distance between all data in the internal resistance sequence of the i-th single energy storage battery and the fitting straight line thereof, the cumulative result of the Pearson similarity coefficient between the internal resistance sequence of the i-th single energy storage battery and the internal resistance sequence of all other single energy storage batteries in the energy storage battery pack.

[0054] The internal resistance abnormality factor reflects the trend fluctuation intensity of the energy storage battery and the correlation of the nonlinear change of the internal resistance caused by the extreme temperature influence and the cluster-level resistance monitoring shielding effect in the battery management system; which represents the nonlinear change trend of the internal resistance data caused by the extreme temperature influence and the temperature conduction effect, which represents the correlation degree of the internal resistance data between the i-th single energy storage battery and other single energy storage batteries. The greater the value of is, the more obvious the trend of the internal resistance change of the single energy storage battery is, the higher the zero-crossing rate of the internal resistance data of the single energy storage battery is, and the more the internal resistance data of the single energy storage battery presents a nonlinear change trend, and the stronger the correlation of the internal resistance data between the single energy storage battery and the remaining single energy storage batteries in the energy storage battery pack is. Therefore, in the running process of the EMS battery management system, the influence of the external extreme temperature on the energy storage battery pack is more serious, and the shielding effect of the internal resistance of the energy storage battery pack on the single energy storage battery is more obvious.

[0055] Further, when the voltage abnormality weight of the energy storage battery is more serious and the internal resistance abnormality factor is more obvious in the running process of the energy storage battery pack, it indicates that the mean value smoothing in the monitoring process of the energy storage battery pack is more serious for the abnormal shielding of the single energy storage battery, and the consistent running state of the energy storage battery pack is worse.

[0056] As a preferred embodiment, according to the internal resistance abnormality factor and the voltage abnormality weight of each single energy storage battery, the running abnormality factor of each single energy storage battery is obtained, which is used to represent the running abnormality degree of each single energy storage battery. The obtaining process of the running abnormality factor of each single energy storage battery is as shown in Figure 2 .

[0057] In this embodiment, the running abnormality factor of the i-th single energy storage battery is denoted as , and its expression is: ; in the formula, is the running abnormality factor of the i-th single energy storage battery; is the voltage abnormality weight of the i-th single energy storage battery in the energy storage battery pack; is the internal resistance shielding abnormality condition of the i-th single energy storage battery in the energy storage battery pack; and norm( ) is a normalization function, so that The value range of the operating abnormality factor is in the range of [0, 1].

[0058] When the operating abnormality factor of the monomer energy storage battery is higher, it indicates that the voltage dispersion condition of the monomer energy storage battery is more obvious, and the response rate consistency of the energy storage battery pack is poorer; at the same time, the internal resistance fluctuation trend of the monomer energy storage battery is stronger, and the nonlinear correlation transformation condition is more obvious, at this time, the battery capacity loss and the overcharge and overdischarge risk are greater, and the acceleration condition of the aging process is more serious.

[0059] Further, a preset abnormal threshold is set, when the number of monomer energy storage batteries in the energy storage battery pack whose operating abnormality factor is greater than or equal to the preset abnormal threshold exceeds a preset proportion, it is considered that the operating balanced consistency of each monomer energy storage battery in the energy storage battery pack is poor, the capacity attenuation and the aging process risk of the monomer energy storage battery are higher, the shielding effect of the energy storage battery pack on the monomer energy storage battery is more serious, the energy storage battery pack is in an operating abnormal state, and the operating state of the energy storage energy management system is poor; on the contrary, it is considered that the operating balanced consistency of each monomer energy storage battery in the energy storage battery pack is good, the capacity attenuation and the aging process risk of the monomer energy storage battery are lower, the energy storage battery pack is not in an operating abnormal state, and the operating state is good. The preset abnormal threshold in the embodiment is 0.6, and the preset proportion is 0.2. .

[0060] At this point, the battery management system operating state evaluation result in the energy storage energy management system can be obtained by the above-mentioned manner, and a kind of energy storage energy management system operating state monitoring method is realized.

[0061] It should be noted that the above-mentioned order of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. And the above describes a specific embodiment of the present description. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0062] Each embodiment in the specification is described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other, and each embodiment focuses on the difference from other embodiments.

[0063] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; modifying the technical solutions described in the above embodiments, or equivalently replacing some technical features, does not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for monitoring the operational status of an energy storage management system, characterized in that, The method includes the following steps: Obtain the voltage and internal resistance sequences of each individual energy storage battery; obtain the voltage and internal resistance sequences of the energy storage battery pack. The voltage change rate sequence of each individual energy storage battery is obtained by considering the voltage change rate within the neighborhood of each abrupt change point in the voltage sequence of each individual energy storage battery. The response rate consistency of each individual energy storage battery is obtained by considering the similarity between the abrupt change point sequence of each individual energy storage battery and the abrupt change point sequence of the energy storage battery pack, as well as the distance between the voltage change rate sequences of each individual energy storage battery and all other individual energy storage batteries. The voltage anomaly weight of each individual energy storage battery is obtained by considering the difference in the dispersion of the voltage sequences of each individual energy storage battery and the energy storage battery pack, as well as the difference in the voltage range of each individual energy storage battery and all other individual energy storage batteries. The internal resistance trend sequence of each individual energy storage battery and energy storage battery pack is obtained by analyzing the trend strength of each internal resistance data in the internal resistance sequence of each individual energy storage battery and energy storage battery pack. The trend fluctuation intensity of each individual energy storage battery is obtained by analyzing the autocorrelation degree of the internal resistance trend sequence of each individual energy storage battery and energy storage battery pack, the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of each individual energy storage battery, and the internal resistance anomaly factor of each individual energy storage battery. The operational anomaly factor of each individual energy storage battery is obtained by combining the voltage anomaly weight of each individual energy storage battery, and then the operational anomaly factor of each individual energy storage battery is obtained, thereby determining whether the energy storage battery pack is operating abnormally.

2. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The process of obtaining the voltage change rate sequence of each individual energy storage battery is as follows: obtain all abrupt change points in the voltage sequence of each individual energy storage battery; record the sequence of all voltage data between each abrupt change point and its preceding abrupt change point in chronological order as the instantaneous voltage sequence of each abrupt change point; record the ratio of the absolute value of the difference between the first and last voltage data of each instantaneous voltage sequence to its duration as the instantaneous voltage change rate of each instantaneous voltage sequence; record the sequence of instantaneous voltage change rates of all instantaneous voltage sequences corresponding to each individual energy storage battery as the voltage change rate sequence of each individual energy storage battery.

3. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The process for obtaining the consistency of the response rate of each individual energy storage battery is as follows: The mutation sequence of each voltage sequence is obtained by determining the position of all mutation points in each voltage sequence; Calculate the consistency of response rate for each individual energy storage cell: In the formula, To ensure the consistency of the response rate of the i-th individual energy storage battery, Let be the cosine similarity between the abrupt change sequence of the voltage sequence of the energy storage battery pack and the abrupt change sequence of the voltage sequence of the i-th individual energy storage battery. It is the cumulative DTW distance between the i-th individual energy storage cell and the voltage change rate sequence of all other individual energy storage cells in the energy storage battery pack.

4. The method for monitoring the operational status of an energy storage management system as described in claim 3, characterized in that, The mutation sequence of each voltage sequence refers to the sequence composed of the positional order of all mutation points in each voltage sequence.

5. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The formula for calculating the voltage anomaly weight of each individual energy storage battery is as follows: In the formula, Let be the voltage anomaly weight for the i-th individual energy storage cell. This is the ratio between the variances of the voltage sequences corresponding to the i-th individual energy storage cell and the energy storage battery pack. It is the sum of the absolute values ​​of the voltage range differences between the i-th individual energy storage cell and all other individual energy storage cells in the energy storage battery pack. To ensure the uniformity of the response rate of the i-th individual energy storage battery, norm() is the normalization function.

6. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The internal resistance trend sequence of each individual energy storage battery and energy storage battery pack refers to the sequence composed of the trend terms of all internal resistance data in the internal resistance sequence of each individual energy storage battery and energy storage battery pack in chronological order.

7. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The formula for calculating the trend fluctuation intensity of each individual energy storage battery is as follows: In the formula, Let represent the trend fluctuation intensity of the i-th individual energy storage battery. , are the Hurst exponents of the internal resistance trend sequences of the i-th individual energy storage battery and the energy storage battery pack, respectively. Let be the zero-crossing rate of the first-order difference sequence of the internal resistance sequence of the i-th single-cell energy storage battery.

8. The method for monitoring the operating status of an energy storage management system as described in claim 1, characterized in that, The formula for calculating the internal resistance anomaly factor of each individual energy storage battery is as follows: In the formula, is the internal resistance anomaly factor of the i-th single-cell energy storage battery; Let represent the trend fluctuation intensity of the i-th individual energy storage battery. This is the sum of the shortest distances between all data points in the internal resistance sequence of the i-th individual energy storage cell and its fitted straight line. It is the sum of the Pearson similarity coefficients between the internal resistance sequence of the i-th individual energy storage cell and all other individual energy storage cells in the energy storage battery pack.

9. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The calculation formula for the operational anomaly factor of each individual energy storage battery is as follows: In the formula, Let be the operational anomaly factor of the i-th individual energy storage battery; The voltage anomaly weight of the i-th individual energy storage cell in the energy storage battery pack; represents the internal resistance shielding anomaly of the i-th individual energy storage cell in the energy storage battery pack; norm() is the normalization function.

10. The method for monitoring the operational status of an energy storage management system as described in claim 1, characterized in that, The specific process for determining whether the energy storage battery pack is operating abnormally is as follows: when the number of individual energy storage batteries in the energy storage battery pack whose operating abnormality factor is greater than or equal to the preset abnormality threshold exceeds the preset proportion, the energy storage battery pack is determined to be in an abnormal operating state. Conversely, it is determined that the energy storage battery pack is not in an abnormal operating state.

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